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Effective robotic interaction with household objects requires the ability to recognize both object instances and object categories. The former are often characterized by locally discriminative texture cues (e.g., instances with prominent brand names and logos), and the latter by salient global shape properties (plates, bowls, pots). We describe experiments with both types of cues, combining a template-and-deformable-parts...
In many scenarios, domestic robot will regularly encounter unknown objects. In such cases, top-down knowledge about the object for detection, recognition, and classification cannot be used. To learn about the object, or to be able to grasp it, bottom-up object segmentation is an important competence for the robot. Also when there is top-down knowledge, prior segmentation of the object can improve...
In this paper we present a method to combine the detection and segmentation of object categories from 3D scenes. In the process, we combine the top-down cues available from object detection technique of Implicit Shape Models and the bottom-up power of Markov Random Fields for the purpose of segmentation. While such approaches have been tried for the 2D image problem domain before, this is the first...
2-D displays present significant visualization deficits and can hinder task performance when accurate perception of depth is required. Navigation of rugged terrain, scouting, and object detection at a distance all present limitations when viewed on traditional 2-D displays. The current investigation presents a novel use of stereo and hyperstereo image pairs to create a 3-D representation of the visual...
We present a method for improving human segmentation results in calibrated, multi-view environments using features derived from both pixel (image) and voxel (volume) space. The main focus of this work is to develop a low-cost, vision-based system for passive activity monitoring of older adults in the home, to capture early signs of illness and functional decline and allow seniors to live independently...
White matter (WM) fiber bundles of the brain can be delineated by diffusion tractography utilizing anatomical regions-of-interest (ROI). These ROIs can specify seed regions in which tract generation algorithms are initiated. Interactive identification of such anatomical ROIs enables the detection of the major WM fiber tracts, but suffers from inter-rater and intra-rater variability, and is time consuming...
In this paper a visual self-localization method for a humanoid robot is presented. This one is based on monocular information. The goal of this method is to obtain the position (x; y) and orientation θ of the humanoid robot inside the field of play. The methods proposed include some digital image processing algorithms and geometric interpretation to perform a 3D monocular reconstruction, that allows...
Through automated agricultural inspection, farmers can potentially achieve better productivity and accurately predict yields and crop quality. A variety of sensors can be used for agricultural inspection, but the cheapest and most information-rich is the video camera. We collect data in the field from a monocular camera fixed to a mobile inspection platform. For purposes of pineapple crop mapping...
Vision-based driver assistance system in complex urban area is highly demanding. The basic requirement for the system is the capacity of detecting potential obstacles. In particular, the automobile, it is more dangerous than other objects. Facing the sensitive area called as “interesting area” in front of the driver within a certain range, this paper presents an object detection method fully using...
Retrieval of near-duplicate image fragments is one of the most challenging problems is CBIR (content-based image retrieval). The objective is to identify almost the same fragments in random images of unpredictable contents. Such fragments usually represent identical object, though captured from a different viewpoint, under different photometric conditions and/or by a different camera. The paper presents...
Liver cancer causes the majority of primary malignant liver tumors among adults. Computed Tomography (CT) scans are generally used to make the treatment plan or to prepare for ablation surgery. Processing CT image includes the automatic diagnosis of liver pathologies, such as detecting lesions and following vessels ramification, and 3D volume rendering. This paper presents a new fully automatic method...
This paper presents a feature extraction method for hand gesture based on multi-layer perceptron. The feature of hand skin color in the YCbCr color space is used to detect hand gesture. The hand silhouette and features can be accurately extracted in means of binarizing the hand image and enhancing the contrast. Median and smoothing filters are integrated to remove the noise. Combinational parameters...
For a Driving Assistance System dedicated to intersection safety, knowledge about the structure and position of the intersection is essential, and detecting the painted road signs can greatly improve this knowledge. This paper describes a method for detection, measurement and classification of painted road objects that are typically found in European intersections. The features of the painted objects...
In the field of environment perception, image segmentation and region classification methods are of high interest. For the development of assistance systems based on the environmental situation, reliable information must be acquired. To achieve robust object detection, algorithms based on laser scanners or time of flight (tof) cameras outperform standard video image based methods. However, for region...
Driver assistance helps save lives. Accurate 3D pose is required to establish if a traffic sign is relevant to the driver. We propose a real-time system that integrates single view detection with region-based 3D tracking of road signs. The optimal set of candidate detections is found, followed by AdaBoost cascades and SVMs. The 2D detections are then employed in simultaneous 2D segmentation and 3D...
In this paper, we present a method for cup boundary detection from monocular colour fundus image to help quantify cup changes. The method is based on anatomical evidence such as vessel bends at cup boundary, considered relevant by glaucoma experts. Vessels are modeled and detected in a curvature space to better handle inter-image variations. Bends in a vessel are robustly detected using a region of...
A system for fast multi-view 3D model reconstruction of object sequences is composed of a number of hardware and software components: the multiple simultaneous image acquisition subsystems, the computation platform, the object/background segmentation algorithm, and in this case, a volumetric carving procedure based on the silhouettes of the objects from each view that generates a volumetric representation...
This paper addresses the problem of identifying the components (such as balconies and windows) of the 3D model of a building. A novel method, based on a voting scheme, is presented for solving such a problem. It is intuitive that interference (such as shadows and occlusions) rarely happen at the same place or at different times when looking at a scene from different directions. In the spirit of this...
A stereo camera based human detection framework for heavy machinery is proposed. The framework allows easy integration of different human detection and image segmentation methods. This integration is essential for diverge and challenging work machine environments, in which traditional, one detector based human detection approaches has been found to be insufficient. The framework is based on the idea...
This paper introduces a brain injury detection approach, using 3D filtering technique, for the images acquired by the magnetic resonance imaging (MRI) technique. The proposed method uses the symmetry property of brain MRI on both 2D images and 3D volumetric information of the MRI sequences. The approach consists of two key steps: (1) each slice of a brain image is segmented into different parts using...
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